With technological advances, institutional stakeholders are considering evidence-based developments such as Curriculum Analytics (CA) to reflect on curriculum and its impact on student learning, dropouts, program quality, and overall educational effectiveness. However, little is known about the CA state of the art in Higher Education Institutions…

Personalized learning (PL) is a student-centered instructional approach in which learning goals, pacing, content, and environments are customized to address individual student needs (Bernacki et al., 2021; Ellis, 2009; Lee, 2014; Miliband, 2006; Office of Educational Technology, 2010; Sota, 2016; Zhang et al., 2020). In grades K-12, PL has been…

The potential of data analytics in higher education is well acknowledged. Yet, there is a notable gap in the literature regarding the practical application of theoretical frameworks for its implementation and evaluation. While research has investigated data analytics for personalised learning, student success prediction, and programme assessment,…

This chapter uses critical perspectives on whiteness to critique higher education's institutional research practice. After briefly describing institutional research, we summarize scholarship about autonomy, ethics, and predictive analytics to illustrate how existing guidance and beliefs about institutional research often dehumanize students by…

While research on Learning Analytics (LA) is plentiful, it often prioritises perspectives on LA systems over the practical ways instructors use data to analyse and refine the learning process per se. The present study addresses this inadequacy by investigating how student data is employed by educators in UK Higher Education Institutions (HEIs) and…

Learning analytics (LA) has become a critical field for transforming educational practices through data-driven insights. This study presents a comprehensive bibliometric analysis of LA research in higher education from 2013 to 2023, utilizing the Scientific Procedures and Rationales for Systematic Literature Review (SPAR-4-SLR) approach. By…

The integration of advanced learning analytics and data-mining technology into higher education has brought various opportunities and challenges, particularly in enhancing students' self-regulated learning (SRL) skills. Analyzing developed features for SRL support, it has become evident that SRL support is not a binary concept but rather a…

Learning analytics is pivotal for supporting learning, with recent research shifting from concepts to reviews. However, understanding factors influencing learning outcomes in higher education through analytics systems remains underexplored. This study aims to fill this gap, providing a holistic view of factors affecting learning outcomes in higher…

Learning analytics (LA) provides insight into student performance and progress, allowing for targeted interventions and support to improve the student learning experience. Uses of LA are diverse, including measuring student engagement, retention, progression, student well-being and curriculum development. This article provides perspectives on the…

Learning analytics provides valuable data to inform the best decisions for each learner. This study, based on adaptive environment (AE) learning analytics dashboards, examines how instructor interventions affect student self-regulation abilities and academic performance. It identifies the self-regulation categories requiring the most support to…

Today, the importance of artificial intelligence in science learning and teaching is rapidly increasing. The growing interest in this field and the resulting increase in academic publications on the subject make it challenging to understand its progress and trends on a global scale. Furthermore, a literature review reveals a notable lack of…

Higher education institutions are increasingly seeking ways to leverage the available educational data to make program and course quality improvements. The development of automated curriculum analytics can play a substantial role in this effort by bringing novel and timely insights into course and program quality. However, the adoption of…

In this study, we examine the role of AI-driven marketing in international student recruitment, focusing on how perceived usefulness, trust, and personalization influence decision-making. Grounded in the Technology Acceptance Model (TAM), the Trust-Based Decision-Making Model, and the Personalization--Privacy Paradox, we studied how AI-powered…

Researchers and practitioners from different disciplines (e.g., educational science, computer science, statistics) continuously enter the rapidly developing research field of learning analytics (LA) and bring along different perspectives and experiences in research design and methodology. Scientific communities share common problems, concepts,…

Education is undergoing critical transformations driven by innovations in remote experimentation and learning analytics. As technology reshapes how we teach and learn, remote experimentation allows students to conduct hands-on, interactive experiments from anywhere in the world, breaking down geographical and resource-based barriers. This shift…